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b/data_org/yolo_dataset/train/labels/998_jpg.rf.a5b998a8d7fe69261274b5b4894beb1b.txt new file mode 100644 index 000000000..e69de29bb diff --git a/data_org/yolo_dataset/train/labels/999_jpg.rf.f1be097ef57a905306ab86a4e4795863.txt b/data_org/yolo_dataset/train/labels/999_jpg.rf.f1be097ef57a905306ab86a4e4795863.txt new file mode 100644 index 000000000..e69de29bb diff --git a/data_org/yolo_dataset/train/labels/99_jpg.rf.7851a89750e8165df3912e183cd15ffa.txt b/data_org/yolo_dataset/train/labels/99_jpg.rf.7851a89750e8165df3912e183cd15ffa.txt new file mode 100644 index 000000000..e69de29bb diff --git a/data_process/data_process.ipynb b/data_process/data_process.ipynb new file mode 100644 index 000000000..8033f34a7 --- /dev/null +++ b/data_process/data_process.ipynb @@ -0,0 +1,130 @@ +{ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "82e802bd", + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "import cv2 as cv\n", + "import json" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "5be9c4de", + "metadata": {}, + "outputs": [], + "source": [ + "img = cv.imread(r\"D:\\lzy\\yolov5\\yolov5\\data_org\\yolo_dataset\\test\\images\\9_jpg.rf.eb8e232922688878a850763f2127e8fd.jpg\")\n" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "9ea190dd", + "metadata": {}, + "outputs": [], + "source": [ + "cv.imshow(\"img\", img)\n", + "if cv.waitKey(0) == ord(\"q\"):\n", + " cv.destroyAllWindows()" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "335bf1ae", + "metadata": {}, + "outputs": [], + "source": [ + "img_folder = r\"D:\\lzy\\yolov5\\yolov5\\data_org\\yolo_dataset\\train\\images\"\n", + "label_path = r\"D:\\lzy\\yolov5\\yolov5\\data_org\\dataset\\train\\_annotations.coco.json\"" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "b8fe5313", + "metadata": {}, + "outputs": [], + "source": [ + "img_path_list = os.listdir(img_folder)\n", + "\n", + "for img_name in img_path_list:\n", + " with open(os.path.join(img_folder.replace(\"images\", \"labels\"), img_name.replace(\".jpg\", \".txt\")), \"w\") as f:\n", + " pass" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "101e48e9", + "metadata": {}, + "outputs": [], + "source": [ + "# 读取文件\n", + "with open(label_path, 'r') as f:\n", + " content = json.load(f)\n", + "pass" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "id": "6edd8ee3", + "metadata": {}, + "outputs": [], + "source": [ + "# 创建一个id到图片名称的映射，以字典形式存储\n", + "dict_id2img = dict()\n", + "for img_info in content['images']:\n", + " dict_id2img[img_info['id']] = img_info['file_name']\n", + "pass" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "a9923894", + "metadata": {}, + "outputs": [], + "source": [ + "# 开始读取标签信息，处理后写入txt文件\n", + "for label_info in content['annotations']:\n", + " img_name = dict_id2img[label_info['image_id']]\n", + " class_name = label_info['category_id']\n", + " x_center = (label_info['bbox'][0] + label_info['bbox'][2] / 2) / 640\n", + " y_center = (label_info['bbox'][1] + label_info['bbox'][3] / 2) / 640\n", + " w = label_info['bbox'][1] / 640\n", + " h = label_info['bbox'][3] / 640\n", + " with open(os.path.join(img_folder.replace(\"images\", \"labels\"), img_name.replace(\".jpg\", \".txt\")), 'a') as f:\n", + " f.write(\"{} {} {} {} {}\\n\".format(class_name, x_center, y_center, w, h))" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "yolov5", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.12.9" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +}